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dc.contributor.authorUlacia Manterola, Alain
dc.contributor.authorSáenz Aguirre, Jon ORCID
dc.contributor.authorIbarra Berastegi, Gabriel
dc.contributor.authorGonzález Rojí, Santos José
dc.contributor.authorCarreno Madinabeitia, Sheila
dc.date.accessioned2017-10-06T15:32:20Z
dc.date.available2017-10-06T15:32:20Z
dc.date.issued2017-09-19
dc.identifier.citationApplied Energyes_ES
dc.identifier.issn0306-2619
dc.identifier.urihttp://hdl.handle.net/10810/22852
dc.description.abstractIn this article, offshore wind energy potential is measured around the Iberian Mediterranean coast and the Balearic Islands using the WRF meteorological model without 3DVAR data assimilation (the N simulation) and with 3DVAR data assimilation (the D simulation). Both simulations have been checked against the observations of six buoys and a spatially distributed analysis of wind based on satellite data (second version of Cross-Calibrated Multi-Platform, CCMPv2), and compared with ERA-Interim (ERAI). Three statistical indicators have been used: Pearson’s correlation, root mean square error and the ratio of standard deviations. The simulation with data assimilation provides the best fit, and it is as good as ERAI, in many cases at a 95% confidence level. Although ERAI is the best model, in the spatially distributed evaluation versus CCMPv2 the D simulation has more consistent indicators than ERAI near the buoys. Additionally, our simulation’s spatial resolution is five times higher than ERAI. Finally, regarding the estimation of wind energy potential, we have represented the annual and seasonal capacity factor maps over the study area, and our results have identified two areas of high potential to the north of Menorca and at Cabo Begur, where the wind energy potential has been estimated for three turbines at different heights according to the simulation with data assimilation.es_ES
dc.description.sponsorshipThis work has been funded by the Spanish Government’s MINECO project CGL2016-76561-R (MINECO/FEDER EU), the University of the Basque Country (project GIU14/03) and the Basque Government (Elkartek 2017 INFORMAR project). SJGR is supported by a FPI Predoctoral Research Grant (MINECO, BES-2014-069977). The ECMWF ERA-Interim data used in this study have been obtained from the ECMWF-MARS Data Server thanks to agreements with ECMWF and AEMET. The authors would like to express their gratitude to the Spanish Port Authorities (Puertos del Estado) for kindly providing data for this study. The computational resources used in the project were provided by I2BASQUE. The authors thank the creators of the WRF/ARW and WRFDA systems for making them freely available to the community. NOAA_OI_SST_V2 data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, through their web-site at http://www.esrl.noaa.gov/psd/ was used in this paper. National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce. 2008, updated daily. NCEP ADP Global Upper Air and Surface Weather Observations (PREPBUFR format), May 1997 – Continuing. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. http://rda.ucar.edu/datasets/ds337.0/ were used. All the calculations have been carried out in the framework of R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/CGL2016-76561-Res_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectOffshore wind energy potential; WRF; WRFDA; Data assimilation; Mesoscale model; Fluid mechanicses_ES
dc.titleUsing 3DVAR data assimilation to measure offshore wind energy potential at different turbine heights in the West Mediterraneanes_ES
dc.typeinfo:eu-repo/semantics/preprintes_ES
dc.rights.holder© 2017 Elsevier Ltd. All rights reserved.es_ES
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S0306261917313144es_ES
dc.identifier.doi10.1016/j.apenergy.2017.09.030
dc.departamentoesFísica aplicada IIes_ES
dc.departamentoesIngeniería nuclear y mecánica de fluidoses_ES
dc.departamentoeuFisika aplikatua IIes_ES
dc.departamentoeuIngeniaritza nuklearra eta jariakinen mekanikaes_ES


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